Junior Machine Learning Engineer

Startupvalleys; Lausanne; Hybrid; CHF 90.000 - 120.000; Vollzeit

Benefits dieser Stelle

Hybrid work model

Zusammenfassung

Giotto.ai in Switzerland is seeking a Junior Machine Learning Engineer (Master's student or recent graduate) to build, test and deploy ML systems based on transformers and reasoning models. You will turn research prototypes into reliable software, working with data pipelines, APIs, and GPU infrastructure while ensuring production readiness.

You will collaborate with researchers and engineers to deploy AI workloads across cloud, on‑premises, and hybrid environments, learning about model

Qualifikationen

• Master's degree in computer science, artificial intelligence, machine learning, software engineering or related field.

Aufgaben

• Develop and maintain Python components for machine learning applications.
• Integrate, fine-tune and evaluate Transformer-based models.
• Help build data-processing, training and inference pipelines.
• Support deployment of models into reliable applications and services.
• Measure and improve model performance, latency and resource usage.
• Write tests and contribute to code quality, documentation and reproducibility.
• Investigate technical problems across models, software and infrastructure.
• Work with researchers to turn experimental code into maintainable systems.

Kenntnisse

Python

PyTorch

LLMs familiarity

Software engineering fundamentals

Testing

Version control

Collaborative mindset

Ausbildung

Master's degree in CS/AI/ML or related field

Tools

Hugging Face

Docker

Kubernetes

Linux

APIs

Jobbeschreibung

Giotto.ai is a Swiss AI company building advanced intelligence systems for Switzerland and Europe. Our portable AI model and operating system enables organisations to use powerful reasoning capabilities while retaining control over their infrastructure, data and operations.

About the role

We are looking for a talented Master’s student or recent graduate to join us as a Junior Machine Learning Engineer.

You will work with our research and engineering teams to build, test and deploy AI systems based on large language and reasoning models. You will help turn research prototypes into reliable software and gain practical experience with model inference, data pipelines, APIs, GPU infrastructure and production deployment.

You will

• Develop and maintain Python components for machine learning applications.


• Integrate, fine-tune and evaluate Transformer-based models.


• Help build data-processing, training and inference pipelines.


• Support the deployment of models into reliable applications and services.


• Measure and improve model performance, latency and resource usage.


• Write tests and contribute to code quality, documentation and reproducibility.


• Investigate technical problems across models, software and infrastructure.


• Work closely with researchers to turn experimental code into maintainable systems.


• Learn how AI workloads are deployed across cloud, private and on-premises infrastructure.

You bring

• A completed or nearly completed Master’s degree in computer science, artificial intelligence, machine learning, software engineering or a related technical field.


• Strong Python programming skills.


• Practical experience with PyTorch or another modern machine learning framework.


• Familiarity with large language models and Transformer architectures.


• Understanding of software-engineering fundamentals, including testing, version control and maintainable code.


• Experience gained through a thesis, internship, university project, open-source contribution or personal project.


• A practical problem-solving mindset and willingness to work across different parts of the technology stack.


• Clear communication skills and a collaborative mindset.

Nice to have

• Experience with Hugging Face, Docker, APIs or Linux.


• Familiarity with vLLM, Ray, Kubernetes or cloud GPU infrastructure.


• Experience deploying a machine learning model or application.


• Understanding of model inference, distributed computing or performance optimisation.


• Experience with CI/CD, experiment tracking or data pipelines.


• Open-source contributions or relevant technical projects.

You do not need several years of professional experience or knowledge of every tool listed above. We are looking for strong engineering foundations, enthusiasm for AI systems and the ability to learn quickly.

Location and work style

This is a full-time position based in Switzerland. We support a hybrid working model, with regular collaboration at our Lausanne office.